Risks.
Named risks, not vague hazards: each entry is a specific, recognised AI risk, with the controls that mitigate it, the clauses that cite it and the sources behind it. 169 risks across 16 categories.
Severity by category
A compact map of the whole register before you filter it.
| Category | critical | high | medium | low | Total |
|---|---|---|---|---|---|
| Governance & Accountability | – | 11 | 10 | – | 21 |
| Model Performance & Reliability | – | 7 | 6 | – | 13 |
| Data Protection & Privacy | 2 | 7 | 4 | – | 13 |
| Fairness, Bias & Impact | – | 4 | 5 | – | 9 |
| Conduct & Customer Outcomes | – | 8 | 4 | – | 12 |
| Transparency & Explainability | – | 2 | 4 | – | 6 |
| Human Factors & Workforce | – | 4 | 3 | – | 7 |
| Model & Application Security | – | 12 | 5 | – | 17 |
| Adversarial ML & Model Integrity | 1 | 4 | 3 | – | 8 |
| Agentic & Autonomous Systems | 1 | 10 | 4 | – | 15 |
| Generative Content & Information Integrity | 1 | 2 | 5 | – | 8 |
| Intellectual Property & Legal Liability | – | 5 | 3 | – | 8 |
| Third-Party & Supply Chain | – | 5 | 4 | – | 9 |
| Operational Resilience | – | 7 | 2 | – | 9 |
| Prohibited & High-Risk Practices | 8 | 1 | – | – | 9 |
| Systemic & Societal | – | 2 | 2 | 1 | 5 |
Browse by list, category or framework
27 of 169 risks shown.
| ID | Risk | Category | Severity |
|---|---|---|---|
| R-030 | AI literacy gap in the deploying organisation Staff who use, rely on or make decisions about AI systems do not understand what those systems can and cannot do, so they misuse or over-trust them. | Human Factors & Workforce | Medium |
| R-021 | AI system lifecycle controls gap The organisation has no defined lifecycle for AI systems, so there is no consistent checkpoint at which a system is assessed, validated, approved, monitored or retired. | Governance & Accountability | Medium |
| R-166 | AI-accelerated cyber threat Advanced models lower the cost and skill needed to find and exploit vulnerabilities, so attacks become faster, more numerous and harder to distinguish from legitimate activity. | Systemic & Societal | High |
| R-040 | AI-driven social scoring An AI system evaluates or classifies people over time on their social behaviour or personal characteristics, and the score leads to detrimental treatment that is out of context or disproportionate. | Prohibited & High-Risk Practices | Critical |
| R-041 | Biometric categorisation of sensitive attributes A biometric categorisation system categorises individuals from their biometric data to deduce or infer race, political opinions, trade union membership, religious or philosophical beliefs, sex life or sexual orientation. | Prohibited & High-Risk Practices | Critical |
| R-169 | Environmental footprint of AI The energy, water and hardware that training and running AI require conflict with the organisation's environmental commitments, or go unmeasured and undisclosed. | Systemic & Societal | Medium |
| R-042 | Exploitation of vulnerable groups by AI An AI system exploits vulnerabilities arising from a person's age, disability or social or economic situation to distort their behaviour in a way that causes, or is likely to cause, significant harm. | Prohibited & High-Risk Practices | Critical |
| R-023 | Inadequate AI resourcing and competence AI systems are adopted without the people, skills, tooling and budget needed to build, oversee and operate them safely. | Governance & Accountability | Medium |
| R-033 | Inadequate AI vendor due diligence An AI supplier is taken on without due diligence proportionate to how material its system is, or with a generic assessment that never asks the questions specific to AI. | Third-Party & Supply Chain | High |
| R-092 | Inadequate board oversight of AI The board and senior management lack the information, expertise or forum to challenge AI risk, and approve what they cannot evaluate. | Governance & Accountability | High |
| R-088 | Incomplete AI inventory The organisation cannot list the AI systems and models it builds, buys or uses, so risk assessment, oversight and regulatory duties are applied to only part of what it has. | Governance & Accountability | High |
| R-043 | Individual criminal risk profiling An AI system assesses or predicts the risk that an individual will commit a criminal offence, based solely on profiling them or on their personality traits and characteristics. | Prohibited & High-Risk Practices | Critical |
| R-165 | Model monoculture and herding Many organisations rely on the same few models, providers and data, so they make the same errors, react in the same way and fail at the same time. | Systemic & Societal | High |
| R-027 | No documented AI policy The organisation uses AI without a policy, approved by top management, that states what is permitted, what is required and who decides. | Governance & Accountability | High |
| R-164 | Non-consensual intimate imagery and child sexual abuse material generation A system is offered or used to generate intimate depictions of identifiable real people without their consent, or child sexual abuse material. | Prohibited & High-Risk Practices | Critical |
| R-109 | Purpose creep in AI data use Data collected for one purpose is used to train or run AI for another purpose that the people concerned would not expect. | Data Protection & Privacy | Medium |
| R-044 | Real-time public biometric identification Real-time remote biometric identification is used in publicly accessible spaces for law enforcement, outside the three narrow objectives and the authorisation the law requires. | Prohibited & High-Risk Practices | Critical |
| R-089 | Shadow AI use Staff use AI tools that have not been approved, placing organisational data and decisions outside any control. | Governance & Accountability | High |
| R-045 | Subliminal or manipulative AI techniques An AI system uses subliminal, purposefully manipulative or deceptive techniques that materially distort a person's behaviour and cause, or are likely to cause, significant harm. | Prohibited & High-Risk Practices | Critical |
| R-129 | Unassessed AI in third-party products A supplier switches on AI features inside a product already in use, bypassing the organisation's assessment and approval. | Third-Party & Supply Chain | High |
| R-029 | Unclear AI ownership and accountability No named individual is accountable for a given AI system, or for AI risk overall, so decisions about it are made by default and nobody answers for the result. | Governance & Accountability | Medium |
| R-091 | Undefined AI risk appetite No statement exists of how much AI risk the organisation will accept, so approvals are inconsistent and nothing triggers escalation. | Governance & Accountability | Medium |
| R-046 | Untargeted facial recognition scraping An AI system creates or expands a facial recognition database through the untargeted scraping of facial images from the internet or from CCTV footage. | Prohibited & High-Risk Practices | Critical |
| R-101 | Untracked regulatory change New or amended AI obligations, including changed application dates, are not identified and translated into controls in time. | Governance & Accountability | Medium |
| R-039 | Vendor concentration and exit strategy gap The organisation depends on a single AI model or supplier for a critical function, with no tested exit plan and no alternative identified. | Third-Party & Supply Chain | High |
| R-163 | Workforce displacement and job quality AI deployment removes roles or makes the remaining work worse, without assessment, involvement of the people affected or a plan for transition. | Human Factors & Workforce | Medium |
| R-047 | Workplace and education emotion recognition An AI system infers the emotions of people at work or in education, for a purpose other than medical or safety reasons. | Prohibited & High-Risk Practices | High |